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REVIEW article

Front. Med.
Sec. Healthcare Professions Education
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1461863
This article is part of the Research Topic Innovations in Teaching and Learning for Health Professions Educators View all 12 articles

The Data-Intensive Research Paradigm: Challenges and Responses in Clinical Professional Graduate Education

Provisionally accepted
Chunhong Yang Chunhong Yang 1Yijing Chen Yijing Chen 2Changshun Qian Changshun Qian 3Fangmin Shi Fangmin Shi 2You Guo You Guo 1*
  • 1 First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
  • 2 Gannan Medical University, Ganzhou, China
  • 3 Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, China

The final, formatted version of the article will be published soon.

    With the widespread application of big data, artificial intelligence, and machine learning technologies in the medical field, a new paradigm of data-intensive clinical research is emerging as a key force driving medical advancement. This new paradigm presents unprecedented challenges for graduate education in clinical professions, encompassing multidisciplinary integration needs, high-quality faculty shortages, learning method transformations, assessment system updates, and ethical concerns. Future healthcare professionals will need not only to possess traditional medical knowledge and clinical skills, but also to master interdisciplinary skills such as data analysis, programming, and statistics. In response, this paper proposes a series of countermeasures, including curriculum reconstruction, faculty development, developing and sharing resources, updating the evaluation and assessment system, and strengthening ethics education. These initiatives aim to help clinical graduate education better adapt to this new paradigm, ultimately cultivating interdisciplinary talents in medical-computer integration.

    Keywords: Data-intensive research, Clinical Medicine, Graduate education, Challenges, response

    Received: 09 Jul 2024; Accepted: 27 Jan 2025.

    Copyright: © 2025 Yang, Chen, Qian, Shi and Guo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: You Guo, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.